Data Scientist

The Data Scientist plays a crucial role in advancing RAFI Microfinance's data-driven decision-making culture. This role is responsible for designing, prototyping, testing, and implementing advanced analytics solutions that support organizational strategies and business needs. The Data Scientist extracts, integrates, and explores data from multiple sources, applies statistical and machine learning methods, and develops predictive and prescriptive models to uncover business value. Beyond technical execution, the role requires the ability to communicate insights effectively, influence stakeholders, and ensure solutions are scalable and aligned with compliance standards. The Data Scientist contributes to innovation, efficiency, and competitiveness by enabling the organization to harness data responsibly and strategically. Main Roles and Responsibilities Data Management Collect, clean, and preprocess data to ensure quality, integrity, and consistency. Build and maintain automated data pipelines for continuous data availability. Analytics & Modeling Design, develop, and test machine learning models and statistical analyses to address business problems. Evaluate, validate, and optimize model performance for accuracy, reliability, and scalability. Collaboration & Stakeholder Engagement Partner with IT, business units, and product owners to translate business requirements into data-driven solutions. Communicate insights, trends, and recommendations through compelling visualizations, reports, and presentations. Innovation & Knowledge Sharing Stay updated on emerging technologies, data science trends, and AI advancements. Support the development of organizational data science standards, documentation, and practices. Contribute to building a culture of data literacy and responsible data use across the organization. Governance & Compliance Ensure adherence to data privacy, security, and governance frameworks. Support risk management by applying best practices in data handling and compliance. Key Skills, Qualifications, and Education Requirements Technical Expertise Proficiency in programming: Python, R, SQL Advanced proficiency in Python and SQL, intermediate proficiency in R Knowledge in machine learning (e.g., TensorFlow) and statistical analysis Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn Experience with data visualization tools : Power BI, Tableau, Looker Familiarity with cloud platforms (Azure, AWS) and big data technologies (Hadoop, Spark) Strong foundation in data governance and data privacy standards Soft Skills Excellent communication and stakeholder management skills Analytical mindset with strong problem-solving abilities Strong organizational and time management skills Ability to explain complex technical concepts to non-technical audiences Education/Background Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or related field Experience in applied data science roles within business or financial services preferred Experience in financial services, banking, or microfinance sector highly preferred but not essential Minimum 3-5 years of experience in applied data science or analytics roles Must be legally authorised to work in the Philippines without sponsorship Competency Profile Technical Data wrangling and data quality assurance Advanced statistical methods (hypothesis testing, regression, time series, A/B testing) Model development, deployment, and evaluation Dashboard design and storytelling with data Cloud computing (Azure, AWS exposure) Automation and workflow scripting Version control and collaboration (e.g., Git) Human Relations Strong leadership and mentoring skills Effective communicator and collaborator across teams Ability to manage stakeholder expectations Personal Attributes God-centered and values-driven Confident, adaptable, and resilient Passionate about data and innovation Mature and grounded in decision-making #J-18808-Ljbffr